i want to query Venue Tips for specific keywords at a larger distance. currently when i do a query the distance is usually between 40-80 kilometers, however if i wanted to calculate a whole country I'd have to do multiple queries.
I've been singling out a particularly created by me in my hometown and adapting the lat and long coordinates, (+/- 40-80 Kilometers) it looks like the distance radius is not uniform, some kind of clusters fundamental to the foursquare data structure.
if i wanted to do a complete search for a country i'd have to define multiple points and hope that i include all of the desired area, also if the the resultset is larger than 500 i'd have to again divide the area to get results on a more granular basis.
my question basically is whether my approach is right or for anyone to provide additional hints
thx in advance.
There's no way to search tips in that large of a area at the moment. That being said, the foursquare venue search behavior is constantly evolving so it's not inconceivable that a larger radius may someday be supported.
If you're building a user application, maybe you can show them a map and let them drag a pin around which then recenters where they're searching.
The maximum supported radius is currently 100,000 meters. That's already a bit more than the 40-80 kilometers you mentioned.
Related
I am a beginner user of Foursquare API.
Most of the Foursquare techniques I learned so far is to do query such as search for or explore from a single location point (e.g. a café or a hotel) in a single geographical coordinate pair of longitude and latitude.
My question is, if it is possible to make an query to explore venues within an area, instead of in the vicinity of a single location point. By ‘an area’, I specifically mean the unit of the administrative division, such as a borough, of a neighbourhood.
In other words, my intending query, if possible, would start from an area specification of the administrative division of my interest (e.g. borough), such as its name or its border’s geographic coordinates—as a 'key' to link with Foursquare data, rather than start from a single location point.
I downloaded GeoJson file that already defined the geographical coordinates of the border of the administrative division of neighbourhoods in a city that I am interested in (link: http://cdn.buenosaires.gob.ar/datosabiertos/datasets/barrios/barrios.geojson). Just FYI, in this link, the neighbourhood is described as ‘barrio’ and the border is defined in the form of 'Polygon'.
I just wonder if I can use an area specification—either the name of an administrative division or a set of the geographic coordinates of an administrative division's border—as a key to make an query about venues such as restaurants, hospitals, and polices within the unit of an administrative division (e.g. borough) from corner to corner.
I guess that the underlying question is if Foursquare side has such info stored in somewhere in its system: if not, my contemplated approach would not work.
Or there might be a totally different workaround to achieve my goal.
If anyone can advise me on this matter, I would highly appreciate it.
Thanks
Given the parameters listed in the docs I think that the best approach would be to use the ll or near parameters and also include a radius so you can limit the search for a given area or region.
To get the middle point for the polygon I guess you would need to do some math but shouldn't be that difficult.
Besides this I think there doesn't seem to be any other parameter in Foursquare API to search by area or by a coordinates array (polygon).
Anyways, I would suggest that you go through the Foursquare API docs for both search and explore endpoints and check for yourself.
since you already have the polygon of interested region:
you could fit many small radius circles within to cover majority of the area.
this is not recommended as it may be rate limited or get you blacklisted but: the foursquare website has a 'draw' tool that allows you to draw a polygon and search venues within. (open networks tab under inspect in your browser and see request) I have noticed that it also can't take very complex polygons, no enclaves, and it further aggressively simplifies polygons to remove holes/dents/land bridges.
here's my demo requests. polygon search isn't strict and might show some venues outside the border.
the url:
https://foursquare.com/explore?mode=url&polygon=35.957999786220704%2C-80.41236877441406%3B35.897393965545646%2C-80.38215637207031%3B35.87847989454576%2C-80.55107116699219%3B35.954664894270834%2C-80.54901123046875%3B35.994118756097%2C-80.386962890625%3B35.957999786220704%2C-80.41236877441406
the corresponding get for venues:
https://api.foursquare.com/v2/search/recommendations?locale=en&explicit-lang=false&v=20210302&m=foursquare&limit=30&intent=bestnearby&polygon=40.8252411857252%2C-74.00630950927733%3B40.817446884558805%2C-73.99772644042969%3B40.81147063339219%2C-73.99875640869139%3B40.80757278825516%2C-74.00768280029297%3B40.80887209540822%2C-74.01729583740234%3B40.81406906961218%2C-74.02175903320312%3B40.8197852710803%2C-74.02210235595702%3B40.826280356677124%2C-74.01695251464844%3B40.8252411857252%2C-74.00630950927733&wsid={}&oauth_token={}
I have coordinates, which are assigned a corresponding geohash in my database. Now I want to retrieve all of the coordinates within two bounding coordinates (top right and top left corner). How can I do that properly?
I tried getting the geohash that fits both of those bounding coordinates, but this solution does not work when they are in completely different regions of the world (so they are not sharing anything in common).
Is there a better way to do that?
Thanks for your help
Unfortunately, this isn't something you can do out-of-the-box with datastore / App engine. (There are no built in spatial queries.)
For early prototyping, etc., you can do it the hard way - retrieve all the rows, and discard the ones not meeting your query in code. Obviously, probably not viable with real production data.
See related question Query for Entities Nearby with Geopt for some possible production solutions.
Having issue when I do document search in index, I use keywords as search param and distance as order by clues in api parameter.
The outcome result has sorted the result by distance, but the keyword based best data never come up into result.
https://****/indexes/IndexName/docs?api-version=2014-10-20-Preview&$filter= geo.distance(geolocation, geography'POINT(-157.825459241867 21.2753200113279)') le 16091.8615317766&search=the beach villas &$orderby=geo.distance(geolocation, geography'POINT(-157.825459241867 21.2753200113279)')&$skip=0&$top=10&$count=true
It is very possible that there is an issue, but I would like to step back and make sure you actually want to use sorting as opposed to scoring profiles. Based on the query, it seems as though what you want to do is boost items that are close to the user. A good way to do this is to use our Distance scoring profile that allows you to provide additional weighting to documents that are closer to the location specified by the user. You can also apply an exponential or linear interpolation to this scoring. Using exponential the villa closest to the location get a really large boost and the further ones get a small boost. Or using linear it is more of a gradual degradation of weighted boosting as it gets farther from the point.
Liam
Please see this page for more details on this: https://msdn.microsoft.com/en-us/library/azure/dn798928.aspx
I'm getting some erratic results from Foursquare's venue search API and I'm wondering if anyone has any tips on how to process my input parameters for the most "intuitive" results.
For example, suppose I am searching for a venue called "Ise Sushi", around "New York, NY", which is equivalent to (lat: 40.7143528, lon: -74.00597309999999) using Google Maps API. Plugging into the Foursquare Venue API, we get:
https://api.foursquare.com/v2/venues/search?query=ise%20sushi&ll=40.7143528%2C-74.00597309999999
This yields pretty underwhelming results: the venue I'm looking for ends up rather far down the list, at 11th place. What's interesting is that reducing the precision of the coordinates appears to produce much better results. For example, suppose we were to round the coordinates to 3 significant digits:
https://api.foursquare.com/v2/venues/search?query=ise%20sushi&ll=40.7%2C-74.0
This time, the venue I'm looking for ends up in 2nd place, even though it is actually farther from the center of the search (1072 meters, vs. 833 meters using the first query).
Another modification that appears to help improve the quality of search is substituting underscores for spaces to separate our search terms. For example, here's the original query with underscores:
https://api.foursquare.com/v2/venues/search?query=ise_sushi&ll=40.7143528%2C-74.00597309999999
This produces the most intuitive-seeming results: the venue I'm looking for appears first, and is accompanied by just one other result, "Ise Restaurant" (which is tagged as a "sushi restaurant"). For what it's worth, this actually seems to be the result set of the same search conducted on Foursquare's own website.
I'm curious what lessons I should be learning from this. Should I be reducing the precision of my coordinates? Should I be connecting my search terms with underscores, and if so, does that limit how a user can order their search terms?
Although there are ranking improvements we can make on our end to find this distant exact match, it generally also helps to specify intent=browse (although it looks like in this case, for now, it may give you worse results). By default, /venues/search uses intent=checkin, which tries really hard to find close-by matches for checking in to, at the expense of other ways a venue might match your search. Learn more at https://developer.foursquare.com/docs/venues/search
I'm working on a project which searches through a database, then sorts the search results by relevance, according to a string the user inputs. I think my current search is fairly decent, but the comparator I wrote to sort the results by relevance is giving me funny results. I don’t know what to consider relevant. I know this is a big branch of information retrieval, but I have no idea where to start finding examples of searches which sort objects by relevance and would appreciate any feedback.
To give a little more background about my specific issue, the user will input a string in a website database, which stores objects (items in the store) with various fields, such as a minor and major classification (for example, an XBox 360 game might be stored with major=video_games and minor=xbox360 fields along with its specific name). The four main fields that I think should be considered in the search are the specific name, major, minor, and genre of the type of object, if that helps.
In case you don't wanna use lucene/Solr, you can always use distance metrics to find the similarity between query and the rows retrieved from database. Once you get the score you can sort them and they will be considered as sorted by relevance.
This is what exactly happens behind the scene of lucene. You can use simple similarity metrics like manhattan distance, distance of points in n-dimensional space etc. Look for lucene scoring formula for more insight.